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Serving an LLM in production with vLLM v1.0.0

Use this resource to deploy a high-throughput LLM API compatible with OpenAI

New

  • 547 downloads
  • 248 likes
  • 179 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install vllm-llm-serving-2

With no option, the skill goes to ~/.agents/skills/; add --agent claude-code (or codex, cursor…) to target an agent.

First time: connect the CLI with

npx --yes palatekit@latest login

The agent guides you through installing vLLM, starting an OpenAI-compatible server, then choosing quantization and tensor parallelism for your GPU. You get deployment commands, a load-testing example and a Docker configuration.

Mostly picked by

Updated November 2, 2026

Card for the “Serving an LLM in production with vLLM” skill

Details

Works in
Install guides
Generates with
Your agent's model
Licence
MIT

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What you get

  • SKILL.md: quick start, requests with the OpenAI SDK and deployment workflows
  • references/optimization.md, quantization.md, server-deployment.md and troubleshooting.md: optimization, quantization and troubleshooting

Good fit for

  • You want to expose a model through an OpenAI-compatible API
  • You serve many requests with limited GPU memory

Not for

    Tags

    • inference
    • api
    • vllm
    • gpu

    About

    You say

    “Deploy Llama 3 8B on my GPU with an OpenAI-compatible API and a load test.”

    Card for the “Serving an LLM in production with vLLM” skill

    Skill published by Orchestra Research under the MIT license, delivered in its original version.

    Show more

    How to use it

    1. Install the skill in your agent's skills folder
    2. Ask your agent to deploy a high-throughput LLM API compatible with OpenAI
    3. Review and adjust the result

    Content preview

    Files

    • LICENSE1.1 KB
    • NOTICE-PALATEKIT.md0.5 KB
    • references/optimization.md5.9 KB
    • references/quantization.md6.9 KB
    • references/server-deployment.md5.4 KB
    • references/troubleshooting.md9.3 KB
    • SKILL.md9.2 KB

    Origin and licence

    Listed unmodified

    Author
    Orchestra Research
    Source
    github.com/orchestra-research/ai-research-skills/tree/773a52944ba4747a18bd4ae9ade53fff041adcbc/12-inference-serving/vllm
    Licence
    MIT

    Notice

    « serving-llms-vllm » (Orchestra Research, MIT) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.

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